Spatial and Temporal Considerations in Vehicle Path Tracking With an Emphasis on Spatial Robustness

This dissertation researches the task and path management of an autonomous vehicle with Ackerman-type steering. The task management problem was approached as a path training operation in which a human operator drives the desired path through an environment. A training trajectory is converted into a series of path segments that are driveable by the autonomous vehicle by first fitting a general path to the dataset. Next, transition segments are added to the general path to match the vehicle velocity and steering angle rate limit. The path management problem has been approached by first deriving a kine- matic model of the vehicle. The time domain model is expressed in the frequency domain and then converted into a spatial frequency domain. Next, a stability crite- rion is derived and used in the synthesis of a spatially-robust path controller

A Modified Linear Integral Resonant Controller for suppressing jump-phenomenon and hysteresis in micro-cantilever beam structures

Credit author statement James MacLean: developed the theory and performed the simulations. Sumeet S. Aphale: supervised the overall research, helped with theoretical development, presentation of results and document formatting.Peer reviewedPostprin